Mid Year 2024

Mid-Year 2024

April 14-16
Orlando, Florida, USA

More info

 

ICPE24

2024 ISPE Annual Meeting

August 24-28
Berlin, Germany

ISPE Updates

The 2024 Mid-Year Meeting Call for Abstracts is now open

Submission deadline: Dec 15
Read the announcement email here
Visit the meeting site page here

The 2024 Call for FISPE applications is now open

Application deadline: Dec 15
Read the announcement email here
Visit the call for applications page here

The 2024 Call for Awards has opened

Submission deadline: Jan 21
Read the announcement email here
Visit the awards page here

The 2024 Call for Board Nominations is now open

Application deadline: Jan 31
Read the announcement email here
Visit the call for nominations page here

ICPE 2023 recordings are now available

Read the announcement email here
Visit the meeting site page here

ICPE 2023 Photos Now Available

Photos of the recently concluded ICPE 2023 held in Halifax, Canada, in August, can be accessed here.

ICPE 2023 photos are royalty-free, and anyone is welcome to download and use them but must be accompanied with attribution to the International Society for Pharmacoepidemiology

Congratulations to our newest ISPE Fellows

ISPE is pleased to announce the induction of 15 new ISPE Fellows this year. The induction ceremony is scheduled for Saturday, August 26th in Halifax, Canada, at ICPE 2023.

Click here for details: New ISPE Fellows 2023

ISPE Social Media (SoMe) Committee

ISPE's SoMe committee manages all ISPE social media accounts. Want something shared or have a suggested post? We'd love to hear from you, submit your ideas to the SoMe committee using this form.

 

Upcoming Webinars:

ISPE Webinar Dec 13, 11:00 AM US EDT

Title: Mind the Gap: A Discussion of Bias and Fairness in Machine Learning for Medicine and Pharmacoepidemiology

Machine learning has the potential to transform aspects of how healthcare and medicine are delivered, yet we know these technologies have the capacity to exacerbate existing inequalities (or introduce new ones).

This webinar will discuss what it means for machine learning algorithms to be fair, explore potential issues, and share concrete steps for creating fair algorithms, as part of our larger goal of promoting equity in health systems. Special attention will be paid to fairness and bias considerations for large language models (e.g., ChatGPT/GPT-4, Bard/LaMDA).

For more details and the registration link please click here.

 

Interested in presenting a webinar? Submit a webinar proposal here

 

 

 

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